#include "WPILib.h" #include #include /** * Example of finding yellow totes based on retroreflective target. * This example utilizes an image file, which you need to copy to the roboRIO * To use a camera you will have to integrate the appropriate camera details with this example. * To use a USB camera instead, see the IntermediateVision example for details * on using the USB camera. To use an Axis Camera, see the AxisCamera example for details on * using an Axis Camera. * * Sample images can be found here: http://wp.wpi.edu/wpilib/2015/01/16/sample-images-for-vision-projects/ */ class VisionRetro2015Sample : public SampleRobot { //A structure to hold measurements of a particle struct ParticleReport { double PercentAreaToImageArea; double Area; double BoundingRectLeft; double BoundingRectTop; double BoundingRectRight; double BoundingRectBottom; }; //Structure to represent the scores for the various tests used for target identification struct Scores { double Area; double Aspect; }; //Images Image *frame; Image *binaryFrame; int imaqError; //Constants Range RING_HUE_RANGE = {101, 64}; //Default hue range for ring light Range RING_SAT_RANGE = {88, 255}; //Default saturation range for ring light Range RING_VAL_RANGE = {134, 255}; //Default value range for ring light double AREA_MINIMUM = 0.5; //Default Area minimum for particle as a percentage of total image area double LONG_RATIO = 2.22; //Tote long side = 26.9 / Tote height = 12.1 = 2.22 double SHORT_RATIO = 1.4; //Tote short side = 16.9 / Tote height = 12.1 = 1.4 double SCORE_MIN = 75.0; //Minimum score to be considered a tote double VIEW_ANGLE = 49.4; //View angle fo camera, set to Axis m1011 by default, 64 for m1013, 51.7 for 206, 52 for HD3000 square, 60 for HD3000 640x480 ParticleFilterCriteria2 criteria[1]; ParticleFilterOptions2 filterOptions = {0,0,1,1}; Scores scores; public: void RobotInit() override { // create images frame = imaqCreateImage(IMAQ_IMAGE_RGB, 0); binaryFrame = imaqCreateImage(IMAQ_IMAGE_U8, 0); //Put default values to SmartDashboard so fields will appear SmartDashboard::PutNumber("Tote hue min", RING_HUE_RANGE.minValue); SmartDashboard::PutNumber("Tote hue max", RING_HUE_RANGE.maxValue); SmartDashboard::PutNumber("Tote sat min", RING_SAT_RANGE.minValue); SmartDashboard::PutNumber("Tote sat max", RING_SAT_RANGE.maxValue); SmartDashboard::PutNumber("Tote val min", RING_VAL_RANGE.minValue); SmartDashboard::PutNumber("Tote val max", RING_VAL_RANGE.maxValue); SmartDashboard::PutNumber("Area min %", AREA_MINIMUM); } void Autonomous() override { while (IsAutonomous() && IsEnabled()) { //read file in from disk. For this example to run you need to copy image.jpg from the SampleImages folder to the //directory shown below using FTP or SFTP: http://wpilib.screenstepslive.com/s/4485/m/24166/l/282299-roborio-ftp imaqError = imaqReadFile(frame, "//home//lvuser//SampleImages//image.jpg", NULL, NULL); //Update threshold values from SmartDashboard. For performance reasons it is recommended to remove this after calibration is finished. RING_HUE_RANGE.minValue = SmartDashboard::GetNumber("Tote hue min", RING_HUE_RANGE.minValue); RING_HUE_RANGE.maxValue = SmartDashboard::GetNumber("Tote hue max", RING_HUE_RANGE.maxValue); RING_SAT_RANGE.minValue = SmartDashboard::GetNumber("Tote sat min", RING_SAT_RANGE.minValue); RING_SAT_RANGE.maxValue = SmartDashboard::GetNumber("Tote sat max", RING_SAT_RANGE.maxValue); RING_VAL_RANGE.minValue = SmartDashboard::GetNumber("Tote val min", RING_VAL_RANGE.minValue); RING_VAL_RANGE.maxValue = SmartDashboard::GetNumber("Tote val max", RING_VAL_RANGE.maxValue); //Threshold the image looking for ring light color imaqError = imaqColorThreshold(binaryFrame, frame, 255, IMAQ_HSV, &RING_HUE_RANGE, &RING_SAT_RANGE, &RING_VAL_RANGE); //Send particle count to dashboard int numParticles = 0; imaqError = imaqCountParticles(binaryFrame, 1, &numParticles); SmartDashboard::PutNumber("Masked particles", numParticles); //Send masked image to dashboard to assist in tweaking mask. SendToDashboard(binaryFrame, imaqError); //filter out small particles float areaMin = SmartDashboard::GetNumber("Area min %", AREA_MINIMUM); criteria[0] = {IMAQ_MT_AREA_BY_IMAGE_AREA, areaMin, 100, false, false}; imaqError = imaqParticleFilter4(binaryFrame, binaryFrame, criteria, 1, &filterOptions, NULL, NULL); //Send particle count after filtering to dashboard imaqError = imaqCountParticles(binaryFrame, 1, &numParticles); SmartDashboard::PutNumber("Filtered particles", numParticles); if(numParticles > 0) { //Measure particles and sort by particle size std::vector particles; for(int particleIndex = 0; particleIndex < numParticles; particleIndex++) { ParticleReport par; imaqMeasureParticle(binaryFrame, particleIndex, 0, IMAQ_MT_AREA_BY_IMAGE_AREA, &(par.PercentAreaToImageArea)); imaqMeasureParticle(binaryFrame, particleIndex, 0, IMAQ_MT_AREA, &(par.Area)); imaqMeasureParticle(binaryFrame, particleIndex, 0, IMAQ_MT_BOUNDING_RECT_TOP, &(par.BoundingRectTop)); imaqMeasureParticle(binaryFrame, particleIndex, 0, IMAQ_MT_BOUNDING_RECT_LEFT, &(par.BoundingRectLeft)); imaqMeasureParticle(binaryFrame, particleIndex, 0, IMAQ_MT_BOUNDING_RECT_BOTTOM, &(par.BoundingRectBottom)); imaqMeasureParticle(binaryFrame, particleIndex, 0, IMAQ_MT_BOUNDING_RECT_RIGHT, &(par.BoundingRectRight)); particles.push_back(par); } sort(particles.begin(), particles.end(), CompareParticleSizes); //This example only scores the largest particle. Extending to score all particles and choosing the desired one is left as an exercise //for the reader. Note that this scores and reports information about a single particle (single L shaped target). To get accurate information //about the location of the tote (not just the distance) you will need to correlate two adjacent targets in order to find the true center of the tote. scores.Aspect = AspectScore(particles.at(0)); SmartDashboard::PutNumber("Aspect", scores.Aspect); scores.Area = AreaScore(particles.at(0)); SmartDashboard::PutNumber("Area", scores.Area); bool isTarget = scores.Area > SCORE_MIN && scores.Aspect > SCORE_MIN; //Send distance and tote status to dashboard. The bounding rect, particularly the horizontal center (left - right) may be useful for rotating/driving towards a tote SmartDashboard::PutBoolean("IsTarget", isTarget); SmartDashboard::PutNumber("Distance", computeDistance(binaryFrame, particles.at(0))); } else { SmartDashboard::PutBoolean("IsTarget", false); } Wait(0.005); // wait for a motor update time } } void OperatorControl() override { while(IsOperatorControl() && IsEnabled()) { Wait(0.005); // wait for a motor update time } } //Send image to dashboard if IMAQ has not thrown an error void SendToDashboard(Image *image, int error) { if(error < ERR_SUCCESS) { DriverStation::ReportError("Send To Dashboard error: " + std::to_string((long)imaqError) + "\n"); } else { CameraServer::GetInstance()->SetImage(binaryFrame); } } //Comparator function for sorting particles. Returns true if particle 1 is larger static bool CompareParticleSizes(ParticleReport particle1, ParticleReport particle2) { //we want descending sort order return particle1.PercentAreaToImageArea > particle2.PercentAreaToImageArea; } /** * Converts a ratio with ideal value of 1 to a score. The resulting function is piecewise * linear going from (0,0) to (1,100) to (2,0) and is 0 for all inputs outside the range 0-2 */ double ratioToScore(double ratio) { return (fmax(0, fmin(100*(1-fabs(1-ratio)), 100))); } double AreaScore(ParticleReport report) { double boundingArea = (report.BoundingRectBottom - report.BoundingRectTop) * (report.BoundingRectRight - report.BoundingRectLeft); //Tape is 7" edge so 49" bounding rect. With 2" wide tape it covers 24" of the rect. return ratioToScore((49/24)*report.Area/boundingArea); } /** * Method to score if the aspect ratio of the particle appears to match the retro-reflective target. Target is 7"x7" so aspect should be 1 */ double AspectScore(ParticleReport report) { return ratioToScore(((report.BoundingRectRight-report.BoundingRectLeft)/(report.BoundingRectBottom-report.BoundingRectTop))); } /** * Computes the estimated distance to a target using the width of the particle in the image. For more information and graphics * showing the math behind this approach see the Vision Processing section of the ScreenStepsLive documentation. * * @param image The image to use for measuring the particle estimated rectangle * @param report The Particle Analysis Report for the particle * @return The estimated distance to the target in feet. */ double computeDistance (Image *image, ParticleReport report) { double normalizedWidth, targetWidth; int xRes, yRes; imaqGetImageSize(image, &xRes, &yRes); normalizedWidth = 2*(report.BoundingRectRight - report.BoundingRectLeft)/xRes; SmartDashboard::PutNumber("Width", normalizedWidth); targetWidth = 7; return targetWidth/(normalizedWidth*12*tan(VIEW_ANGLE*M_PI/(180*2))); } }; START_ROBOT_CLASS(VisionRetro2015Sample);